Clear Secure Beneish M-Score Historical Data
The historical data trend for Clear Secure's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Clear Secure Beneish M-Score Chart
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Clear Secure Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
1.18 |
-3.86 |
-3.73 |
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Clear Secure Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-3.86 |
-4.07 |
-4.15 |
-3.82 |
-3.73 |
Competitive Comparison of Clear Secure's Beneish M-Score
For the Software - Application subindustry, Clear Secure's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Clear Secure's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Clear Secure's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Clear Secure's Beneish M-Score falls into.
Clear Secure Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Clear Secure for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 0.3207 | + | 0.528 * 1.0146 | + | 0.404 * 0.8395 | + | 0.892 * 1.4027 | + | 0.115 * 0.866 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.5926 | + | 4.679 * -0.189841 | - | 0.327 * 1.2798 |
| = | -3.73 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $0.5 Mil.
Revenue was 170.965 + 160.387 + 149.871 + 132.356 = $613.6 Mil.
Gross Profit was 105.859 + 102.165 + 94.448 + 79.64 = $382.1 Mil.
Total Current Assets was $770.0 Mil.
Total Assets was $1,045.0 Mil.
Property, Plant and Equipment(Net PPE) was $178.5 Mil.
Depreciation, Depletion and Amortization(DDA) was $21.6 Mil.
Selling, General, & Admin. Expense(SGA) was $265.9 Mil.
Total Current Liabilities was $552.0 Mil.
Long-Term Debt & Capital Lease Obligation was $121.7 Mil.
Net Income was 13.975 + 15.346 + 4.011 + -5.224 = $28.1 Mil.
Non Operating Income was -0.108 + 0.661 + 0.634 + 0.274 = $1.5 Mil.
Cash Flow from Operations was 94.131 + -4.86 + 75.005 + 60.757 = $225.0 Mil.
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Total Receivables was $1.2 Mil.
Revenue was 128.253 + 115.919 + 102.723 + 90.539 = $437.4 Mil.
Gross Profit was 81.608 + 74.258 + 65.097 + 55.417 = $276.4 Mil.
Total Current Assets was $741.6 Mil.
Total Assets was $1,037.5 Mil.
Property, Plant and Equipment(Net PPE) was $181.8 Mil.
Depreciation, Depletion and Amortization(DDA) was $18.8 Mil.
Selling, General, & Admin. Expense(SGA) was $319.9 Mil.
Total Current Liabilities was $397.5 Mil.
Long-Term Debt & Capital Lease Obligation was $125.1 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (0.526 / 613.579) | / | (1.169 / 437.434) |
| = | 0.000857 | / | 0.002672 |
| | = | 0.3207 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (276.38 / 437.434) | / | (382.112 / 613.579) |
| = | 0.631821 | / | 0.622759 |
| | = | 1.0146 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (770.034 + 178.485) / 1045.009) | / | (1 - (741.6 + 181.804) / 1037.517) |
| = | 0.092334 | / | 0.109987 |
| | = | 0.8395 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 613.579 | / | 437.434 |
| | = | 1.4027 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (18.792 / (18.792 + 181.804)) | / | (21.649 / (21.649 + 178.485)) |
| = | 0.093681 | / | 0.108173 |
| | = | 0.866 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (265.881 / 613.579) | / | (319.853 / 437.434) |
| = | 0.433328 | / | 0.731203 |
| | = | 0.5926 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((121.655 + 552.049) / 1045.009) | / | ((125.146 + 397.473) / 1037.517) |
| = | 0.644687 | / | 0.503721 |
| | = | 1.2798 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (28.108 - 1.461 | - | 225.033) | / | 1045.009 |
| | = | -0.189841 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Clear Secure has a M-score of -3.73 suggests that the company is unlikely to be a manipulator.
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